Modern markets are saturated by user driven data consumption. Applications integrate media and user information from variety of sources to congregate resources in order to meet customer demand. Video and audio information consume warehouses of systems providing instantaneous access to user data across the world. User organized information require resource intensive systems to accommodate the demand. In addition, enterprise requirements complicate information storage and retrieval by inserting business requirements into the storage systems. Relational data in enterprise systems require extensive relational mapping. Alterations to the existing data systems require re-execution of processes to map new relations. Each relational update may take away from resources needed for other demand.
Storing graphs (e.g. user's memberships to distribution groups) in a relational store is in high technical demand. Modern solutions are unable to store graph data efficiently. Systems are slow to computationally read graph data. Directory systems in enterprise businesses frequently implement graph based relational technologies. Graphs are widely used to define relationships between users and distribution groups or security groups. If there is a link between a user and a group, systems consider the user belonging to the group.
A current preferable relational technology is Active Directory® by Microsoft Corporation of Redmond, Wash. Extending Active Directory to support multi-tenancy in a cloud based system is an increasingly difficult challenge. Each additional node in a graph may complicate the resources and processes to efficiently map the relationships between the nodes.